TY - JOUR
T1 - Exponentiated power Lindley power series class of distributions
T2 - Theory and applications
AU - Alizadeh, M.
AU - Bagheri, S. F.
AU - Samani, E. Bahrami
AU - Ghobadi, S.
AU - Nadarajah, S.
PY - 2017
Y1 - 2017
N2 - We introduce a new four-parameter generalization of the exponentiated power Lindley (EPL) distribution, called the exponentiated power Lindley power series (EPLPS) distribution. The new distribution arises on a latent complementary risks scenario, in which the lifetime associated with a particular risk is not observable; rather, we observe only the minimum lifetime value among all risks. The distribution exhibits a variety of bathtub-shaped hazard rate functions. It contains as particular cases several lifetime distributions. Various properties of the distribution are investigated including closed-form expressions for the density function, cumulative distribution function, survival function, hazard rate function, the rth raw moment, and also the moments of order statistics. Expressions for the Rényi and Shannon entropies are also given. Moreover, we discuss maximum likelihood estimation and provide formulas for the elements of the Fisher information matrix. Finally, two data applications are given showing flexibility and potentiality of the EPLPS distribution.
AB - We introduce a new four-parameter generalization of the exponentiated power Lindley (EPL) distribution, called the exponentiated power Lindley power series (EPLPS) distribution. The new distribution arises on a latent complementary risks scenario, in which the lifetime associated with a particular risk is not observable; rather, we observe only the minimum lifetime value among all risks. The distribution exhibits a variety of bathtub-shaped hazard rate functions. It contains as particular cases several lifetime distributions. Various properties of the distribution are investigated including closed-form expressions for the density function, cumulative distribution function, survival function, hazard rate function, the rth raw moment, and also the moments of order statistics. Expressions for the Rényi and Shannon entropies are also given. Moreover, we discuss maximum likelihood estimation and provide formulas for the elements of the Fisher information matrix. Finally, two data applications are given showing flexibility and potentiality of the EPLPS distribution.
KW - Hazard rate function
KW - Maximum likelihood estimation
KW - Model selection criteria
KW - Power series distributions
KW - Residual life function.
UR - http://www.scopus.com/inward/record.url?scp=85027174350&partnerID=8YFLogxK
U2 - 10.1080/03610918.2017.1350270
DO - 10.1080/03610918.2017.1350270
M3 - Article
AN - SCOPUS:85027174350
SN - 0361-0918
SP - 1
EP - 33
JO - Communications in Statistics: Simulation and Computation
JF - Communications in Statistics: Simulation and Computation
ER -